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Record W2032046616 · doi:10.1002/ppp.579

The effect of transient conditions on an equilibrium permafrost‐climate model

2007· article· en· W2032046616 on OpenAlexaff
D W Riseborough

Bibliographic record

VenuePermafrost and Periglacial Processes · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsPermafrostActive layerClimatologyGlobal warmingEnvironmental scienceClimate changeAtmospheric sciencesSnowTable (database)GeologyGeomorphologyMaterials science

Abstract

fetched live from OpenAlex

Abstract Equilibrium permafrost models assume a stationary temperature and snow‐cover climate. With a variable or changing climate, short‐term energy imbalances between the active layer and permafrost result in transient departures from the equilibrium condition. This study examines the effects of such variability on an equilibrium permafrost‐climate model, the temperature at the top of permafrost (TTOP) model. Comparisons between numerical results and temperatures predicted by the TTOP‐model suggest that stationary inter‐annual variability introduces an error in the top‐of‐permafrost temperature obtained with the equilibrium model that is higher where permafrost temperature is close to 0°C, although multi‐year averaging reduces the error to 0.1°C or less. In the presence of a warming trend, the equilibrium model prediction tracked the changing top‐of‐permafrost temperature until permafrost temperatures reached 0°C, after which the equilibrium model produced significant errors. Errors up to 1°C were due to the temperature gradient through the developing talik, and depended on the warming rate, and the thickness of the talik. For all warming rates, the error was largest when the permafrost table was about 4 m below the surface, with the error declining as the permafrost table fell. Copyright © 2007 John Wiley & Sons, Ltd.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.275
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations36
Published2007
Admission routes1
Has abstractyes

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